219 research outputs found
Multi-stage sizing approach for development of utility-scale BESS considering dynamic growth of distributed photovoltaic connection
The battery energy storage system (BESS) is regarded as one of the most promising address operational challenges caused by distributed generations. This paper proposes a novel multi-stage sizing model for utility-scale BESS, to optimize the BESS development strategies for distribution networks with increasing penetration levels and growth patterns of dispersed photovoltaic (PV) panels. Particularly, an integrated model is established in order to accommodate dispersed PVs in short-term operation scale while facilitating appropriate profits in long-term planning scale. Clusterwise reduction is adopted to extract the most representative operating scenarios with PVs and BESS integration, which is able to decrease the computing complexity caused by scenario redundancy. The numerical studies on IEEE 69-bus distribution system verify the feasibility of the proposed multi-stage sizing approach for the utility-scale BESS.</p
An explicit formula based estimation method for distribution network reliability
An improved explicit estimation algorithm is proposed for reliability estimation of distribution network. Firstly, hierarchical clustering is used to identify and cluster typical feeders based on topology structure. Secondly, the explicit formula of reliability indices under each typical feeder topology is derived by regression analysis, to establish the model for network reliability estimation. Numerical simulations show the suitability of the proposed method in obtaining accurate reliability index for diversified network topology
Towards a "Swiss Army Knife" for Scalable User-Defined Temporal -Core Analysis
Querying cohesive subgraphs on temporal graphs (e.g., social network, finance
network, etc.) with various conditions has attracted intensive research
interests recently. In this paper, we study a novel Temporal
-Core Query (TXCQ) that extends a fundamental Temporal
-Core Query (TCQ) proposed in our conference paper by optimizing or
constraining an arbitrary metric of -core, such as size,
engagement, interaction frequency, time span, burstiness, periodicity, etc. Our
objective is to address specific TXCQ instances with conditions on different
in a unified algorithm framework that guarantees scalability. For
that, this journal paper proposes a taxonomy of measurement
and achieve our objective using a two-phase framework
while is time-insensitive or time-monotonic. Specifically,
Phase 1 still leverages the query processing algorithm of TCQ to induce all
distinct -cores during a given time range, and meanwhile locates the "time
zones" in which the cores emerge. Then, Phase 2 conducts fast local search and
evaluation in each time zone with respect to the time
insensitivity or monotonicity of . By revealing two
insightful concepts named tightest time interval and loosest time interval that
bound time zones, the redundant core induction and unnecessary
evaluation in a zone can be reduced dramatically. Our experimental results
demonstrate that TXCQ can be addressed as efficiently as TCQ, which achieves
the latest state-of-the-art performance, by using a general algorithm framework
that leaves as a user-defined function
Formulation of locational marginal electricity-carbon price in power systems
Decarbonisation of power systems is essential for realising carbon neutrality, in which the economic cost caused by carbon is needed to be qualified. Based on the formulation of locational marginal price (LMP), this paper proposes a locational marginal electricity-carbon price (EC-LMP) model to reveal carbon-related costs caused by power consumers. A carbon-price-integrated optimal power flow (C-OPF) is then developed to maximise the economic efficiency of the power system considering the costs of electricity and carbon. Case studies are presented to demonstrate the new formulation and the results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy
Formulation of Locational Marginal Electricity-Carbon Price in Power Systems
Decarbonisation of power systems is essential for realising carbon neutrality, in which the economic cost caused by carbon is needed to be qualified. Based on the formulation of locational marginal price (LMP), this paper proposes a locational marginal electricity-carbon price (EC-LMP) model to reveal carbon-related costs caused by power consumers. A carbon-price-integrated optimal power flow (C-OPF) is then developed to maximise the economic efficiency of the power system considering the costs of electricity and carbon. Case studies are presented to demonstrate the new formulation and the results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy
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